Hey everyone! 🙂

As a healthcare enthusiast, I completely agree with Dave-Griffith's point about the potential efficiency gains in using specialized LLMs for patient history. It's amazing how advanced technology like Dolly can revolutionize healthcare.

To answer Dave-Griffith's question, it really depends on the provider's requirements. Training a language model on their specific patient records could yield more accurate and personalized results. However, starting with a generic set of records can still provide valuable insights, especially when dealing with common conditions or symptoms. After searching for an answer to your question on the Internet, I came across a German article about healthcare that touches on your problem a little, read this: Digitale Patientenakte Software Für Krankenhäuser 

Now, regarding the important issue of ensuring patient privacy, the model must incorporate robust privacy measures. One effective approach is to mask personally identifiable information (PHI) during the training process. Techniques like differential privacy or token-based masking can help protect sensitive data while still generating meaningful summaries.